By Wei Tsang Ooi, Cees G.M. Snoek, Hung Khoon Tan, Chin Kuan Ho, Benoit Huet, Chong-Wah Ngo
This e-book constitutes the refereed court cases of the fifteenth Pacific Rim convention on Multimedia, PCM 2014, held in Kuching, Malaysia, in December 2014. The 35 revised complete papers and six brief papers offered have been rigorously reviewed and chosen from eighty four submissions. The papers disguise quite a lot of issues within the region of multimedia content material research, multimedia sign processing and communications, and multimedia purposes and providers. they've been equipped into topical sections on video coding, annotation, snapshot and picture, functions, humans, picture research and processing lower than additional support, nearest neighbor, neural networks, and audio. additionally integrated are sections with top papers and posters and demonstrations.
Read or Download Advances in Multimedia Information Processing – PCM 2014: 15th Pacific-Rim Conference on Multimedia, Kuching, Malaysia, December 1-4, 2014, Proceedings PDF
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Additional info for Advances in Multimedia Information Processing – PCM 2014: 15th Pacific-Rim Conference on Multimedia, Kuching, Malaysia, December 1-4, 2014, Proceedings
024 seconds to recognize one image and it achieved about 83% classification rate within the top five candidates. In the experiments, we report the results of our food photo mining on 100 kinds of foods in the UEC-FOOD100 dataset from the photo tweet log data we have collected for two years and four months. As results, we detected about 470,000 food photos from Twitter with about 99% accuracy. With this data, we have made spatio-temporal analysis on food photos. In addition, we have implemented the real-time food photo detection system from the Twitter stream.
Acknowledgments. The authors are grateful to the ImageCLEF coordinators especially dr. Mauricio Villegas for helping evaluate our results. This research was supported by the Fundamental Research Funds for the Central Universities and the Research Funds of Renmin University of China (No. 14XNLQ01), NSFC (No. 61303184), SRFDP (No. 20130004120006), BJNSF (No. 4142029), SRF for ROCS, SEM, and Shanghai Key Laboratory of Intelligent Information Processing, China (Grant No. IIPL-2014-002). Appendix ImageCLEF 2014 annotation vocabulary.
However, separating specular edge from input image is under-constrained and existing methods require user assistance or handle only simple scenes. This paper presents an iterative weighted Specular-Edge color constancy scheme that leverages large database of images gathered from the web. Given an input image, we execute an efficient visual search to find the closest visual context from the database and use the visual context as an image-specific prior. This prior is then used to correct the chromaticity of the input image before illumination estimation.